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O-scan is a Magnetic Resonance (MR) system that produces transversal, sagittal and coronal and oblique cross-section images of the limbs and joints. It is intended for imaging portions of the arm, including the hand, wrist, forearm and elbow, but excluding the upper arm, and imaging portions of the leg, including the foot, ankle, calf and knee, but excluding the thigh.

O-scan images correspond to the spatial distribution of protons (hydrogen nuclei) that determine magnetic resonance properties and are dependent on the MR parameters, including spin-lattice relaxation time (T1), spin-spin relaxation time (T2), nuclei density, flow velocity and "chemical shift". When interpreted by a medical expert trained in the use of MR equipment, the images can provide diagnostically useful information.

O-scan is a Magnetic Resonance (MR) system, which produces images of the internal structures of the patient's limbs and joints.

The system comprises three main parts:

1. Magnetic unit, containing a permanent magnet

2. Electronic unit

3. Console, comprising a PC, Keyboard, mouse, monitor and operating table.

4. Patient seat

5. Receiving coils

This 510(k) summary for the O-Scan MR System does not contain detailed acceptance criteria or a specific study proving the device meets acceptance criteria in the manner typically expected for AI/ML-driven medical devices. Instead, it focuses on demonstrating substantial equivalence to predicate devices for a conventional MRI system.

Here's an analysis based on the provided text, highlighting what is present and what is absent:

1. Table of Acceptance Criteria and Reported Device Performance:

The document states: "Non-clinical testing of the O-Scan system demonstrated that it met performance requirements and is as safe and effective as the predicate devices."

This is a general statement of compliance, but no specific quantitative acceptance criteria (e.g., sensitivity, specificity, accuracy thresholds) or detailed reported device performance metrics are provided. For a traditional MRI system, "performance requirements" would typically refer to image quality parameters, signal-to-noise ratio, spatial resolution, field homogeneity, etc., but these are not explicitly listed or quantified in this summary.

2. Sample Size Used for the Test Set and Data Provenance:

Not specified. The document mentions "non-clinical testing," which usually refers to phantom studies, engineering tests, and bench testing, rather than studies on patient data with a defined "test set" in the context of AI/ML evaluation.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications:

Not applicable/Not specified. For a conventional MRI system's substantial equivalence review, a dedicated "test set" with expert-established ground truth for diagnostic accuracy (as would be needed for an AI algorithm) is not typically detailed in this type of summary. The images are to be "interpreted by a medical expert trained in the use of MR equipment" for diagnostic information.

4. Adjudication Method for the Test Set:

Not applicable/Not specified. As there's no defined "test set" for diagnostic accuracy evaluation in the AI/ML sense, no adjudication method is mentioned.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

No. This document describes a conventional MRI system, not an AI-assisted diagnostic tool. Therefore, an MRMC study to show human reader improvement with AI assistance is not relevant and was not performed.

6. Standalone Performance Study:

No. The O-Scan is a diagnostic imaging device that produces images. Its performance is inherent in the image quality it generates for human interpretation, not in an automated diagnostic output from an algorithm operating in a standalone mode.

7. Type of Ground Truth Used:

Not applicable/Not specified. For evaluating the O-Scan as a diagnostic imaging system, the "ground truth" would ultimately be the patient's clinical outcome or other diagnostic modalities, as interpreted by a medical expert. However, the 510(k) summary doesn't detail a study where diagnostic accuracy against a specific ground truth was performed or quantified for the O-Scan itself. Its approval is based on substantial equivalence to existing MRI systems.

8. Sample Size for the Training Set:

Not applicable. The O-Scan is a hardware device (MRI scanner), not a machine learning algorithm. Therefore, there is no "training set" in the AI/ML context.

9. How the Ground Truth for the Training Set Was Established:

Not applicable. As there is no training set for an AI algorithm, this information is not relevant.

Summary of what is available from the 510(k) in relation to the request for AI/ML device criteria:

The provided 510(k) summary is for a traditional Magnetic Resonance (MR) imaging system (a hardware device), not an AI/ML-driven diagnostic software. Consequently, most of the requested information, which pertains to the rigorous evaluation of AI/ML algorithms, is not present because it is not applicable to the type of device being described.

The "performance data" section is very brief, simply stating that "Non-clinical testing of the O-Scan system demonstrated that it met performance requirements and is as safe and effective as the predicate devices." This is typical for demonstrating substantial equivalence for a conventional medical imaging device, focusing on engineering specifications and comparison to existing, cleared devices rather than a detailed clinical performance study with specific diagnostic accuracy metrics or AI algorithm validation.

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